Managing eGovernment Information Resources Using Faceted Taxonomy

Abstract

The rapid development of information technology in recent years has caused a severe increase in the amount of communication between citizens and government, which led to a considerable upsurge in the volume and complexity of information in eGovernment systems. As a result, structuring information has become a critical topic. When considering structuring information in eGovernment systems, it is important to have in mind two very important processes in the work of eGovernment: analyzing current situation and decision making. For successful completion of these processes, holistic understanding of the situation is necessary. This paper proposes a model that will ease the process of analyzing current situation and the process of decision-making, by providing a holistic view of the situation to the employees in eGovernment. The model effectively manages information and endows decision makers, and other employees in eGovernment, with relevant pieces of information. It also facilitates the understanding of relationships between different pieces of information in the system. The model is based on faceted taxonomy. Faceted taxonomy represents a set of taxonomies, each one describing the domain of interest from a different, preferably orthogonal, point of view. Faceted taxonomy allows rich information structuring and allows users to easily correlate concepts and explore correlations between these concepts. This approach can also provide an intuitive, hierarchical, visual representation of relations between concepts. Visual representations can help better understanding complex topics. The model provides a strong foundation for further development of visualizing techniques. Using this model can also improve all search and browsing methods on the information in the system, and allow easy transformations on the structure. This paper clarifies the criteria selection process for the taxonomies used in the model and provides guidelines for practical implementation of the model. The model also offers recommendations for further exploration of this field.